mobowuhan/DevSecOpsKB

1from llama_index import SimpleDirectoryReader, LLMPredictor, PromptHelper, StorageContext, ServiceContext, GPTVectorStoreIndex, load_index_from_storage2from langchain.chat_models import ChatOpenAI3import gradio as gr4import sys5import os6os.environ["OPENAI_API_KEY"] = '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'7 8def create_service_context():9    #constraint parameters10    max_input_size = 409611    num_outputs = 51212    max_chunk_overlap = 113    chunk_size_limit = 60014    #allows the user to explicitly set certain constraint parameters15    prompt_helper = PromptHelper(max_input_size, num_outputs, max_chunk_overlap, chunk_size_limit=chunk_size_limit)16    #LLMPredictor is a wrapper class around LangChain's LLMChain that allows easy integration into LlamaIndex17    llm_predictor = LLMPredictor(llm=ChatOpenAI(temperature=0.5, model_name="gpt-3.5-turbo", max_tokens=num_outputs))18    #constructs service_context19    service_context = ServiceContext.from_defaults(llm_predictor=llm_predictor, prompt_helper=prompt_helper)20    return service_context21 22def data_ingestion_indexing(directory_path):23    #loads data from the specified directory path24    documents = SimpleDirectoryReader(directory_path).load_data()25    26    #when first building the index27    index = GPTVectorStoreIndex.from_documents(28        documents, service_context=create_service_context()29    )30    #persist index to disk, default "storage" folder31    index.storage_context.persist()32    return index33 34def data_querying(input_text):35    #rebuild storage context36    storage_context = StorageContext.from_defaults(persist_dir="./storage")37    #loads index from storage38    index = load_index_from_storage(storage_context, service_context=create_service_context())39    40    #queries the index with the input text41    response = index.as_query_engine().query(input_text)42    43    return response.response44 45iface = gr.Interface(fn=data_querying,46                     inputs=gr.components.Textbox(lines=7, label="Enter your question"),47                     outputs="text",48                     title="Wenqi's Custom-trained DevSecOps Knowledge Base")49#passes in data directory50index = data_ingestion_indexing("data")51iface.launch(share=True)52